{"action":"created","issue":{"url":"https://api.github.com/repos/Franck-Dernoncourt/NeuroNER/issues/83","repository_url":"https://api.github.com/repos/Franck-Dernoncourt/NeuroNER","labels_url":"https://api.github.com/repos/Franck-Dernoncourt/NeuroNER/issues/83/labels{/name}","comments_url":"https://api.github.com/repos/Franck-Dernoncourt/NeuroNER/issues/83/comments","events_url":"https://api.github.com/repos/Franck-Dernoncourt/NeuroNER/issues/83/events","html_url":"https://github.com/Franck-Dernoncourt/NeuroNER/issues/83","id":280725679,"number":83,"title":"AttributeError: 'PolyCollection' object has no attribute 'get_axes'","user":{"login":"pengyu","id":1018252,"avatar_url":"https://avatars3.githubusercontent.com/u/1018252?v=4","gravatar_id":"","url":"https://api.github.com/users/pengyu","html_url":"https://github.com/pengyu","followers_url":"https://api.github.com/users/pengyu/followers","following_url":"https://api.github.com/users/pengyu/following{/other_user}","gists_url":"https://api.github.com/users/pengyu/gists{/gist_id}","starred_url":"https://api.github.com/users/pengyu/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/pengyu/subscriptions","organizations_url":"https://api.github.com/users/pengyu/orgs","repos_url":"https://api.github.com/users/pengyu/repos","events_url":"https://api.github.com/users/pengyu/events{/privacy}","received_events_url":"https://api.github.com/users/pengyu/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2017-12-09T14:53:08Z","updated_at":"2017-12-09T14:54:49Z","closed_at":null,"author_association":"NONE","body":"I see the following error. Is there a way to fix it? Thanks.\r\n\r\n```\r\n~/linux/test/python/nlpdl/NeuroNER/src$ python3 main.py\r\nNeuroNER version: 1.0-dev\r\nTensorFlow version: 1.4.0\r\n{'character_embedding_dimension': 25,\r\n 'character_lstm_hidden_state_dimension': 25,\r\n 'check_for_digits_replaced_with_zeros': 1,\r\n 'check_for_lowercase': 1,\r\n 'dataset_text_folder': '../data/conll2003/en',\r\n 'debug': 0,\r\n 'dropout_rate': 0.5,\r\n 'experiment_name': 'test',\r\n 'freeze_token_embeddings': 0,\r\n 'gradient_clipping_value': 5.0,\r\n 'learning_rate': 0.005,\r\n 'load_all_pretrained_token_embeddings': 0,\r\n 'load_only_pretrained_token_embeddings': 0,\r\n 'main_evaluation_mode': 'conll',\r\n 'maximum_number_of_epochs': 100,\r\n 'number_of_cpu_threads': 8,\r\n 'number_of_gpus': 0,\r\n 'optimizer': 'sgd',\r\n 'output_folder': '../output',\r\n 'parameters_filepath': './parameters.ini',\r\n 'patience': 10,\r\n 'plot_format': 'pdf',\r\n 'pretrained_model_folder': '../trained_models/conll_2003_en',\r\n 'reload_character_embeddings': 1,\r\n 'reload_character_lstm': 1,\r\n 'reload_crf': 1,\r\n 'reload_feedforward': 1,\r\n 'reload_token_embeddings': 1,\r\n 'reload_token_lstm': 1,\r\n 'remap_unknown_tokens_to_unk': 1,\r\n 'spacylanguage': 'en',\r\n 'tagging_format': 'bioes',\r\n 'token_embedding_dimension': 100,\r\n 'token_lstm_hidden_state_dimension': 100,\r\n 'token_pretrained_embedding_filepath': '../data/word_vectors/glove.6B.100d.txt',\r\n 'tokenizer': 'spacy',\r\n 'train_model': 1,\r\n 'use_character_lstm': 1,\r\n 'use_crf': 1,\r\n 'use_pretrained_model': 0,\r\n 'verbose': 0}\r\nFormatting train set from CONLL to BRAT... Done.\r\nConverting CONLL from BIO to BIOES format... Done.\r\nFormatting valid set from CONLL to BRAT... Done.\r\nConverting CONLL from BIO to BIOES format... Done.\r\nFormatting test set from CONLL to BRAT... Done.\r\nConverting CONLL from BIO to BIOES format... Done.\r\nLoad dataset... done (93.21 seconds)\r\nLoad token embeddings... done (0.43 seconds)\r\nnumber_of_token_original_case_found: 14618\r\nnumber_of_token_lowercase_found: 11723\r\nnumber_of_token_digits_replaced_with_zeros_found: 119\r\nnumber_of_token_lowercase_and_digits_replaced_with_zeros_found: 16\r\nnumber_of_loaded_word_vectors: 26476\r\ndataset.vocabulary_size: 28984\r\n\r\nStarting epoch 0\r\nTraining completed in 0.00 seconds\r\nEvaluate model on the train set\r\nprocessed 203621 tokens with 23499 phrases; found: 198223 phrases; correct: 3218.\r\naccuracy:   3.71%; precision:   1.62%; recall:  13.69%; FB1:   2.90\r\n              LOC: precision:   1.32%; recall:   2.77%; FB1:   1.79  14951\r\n             MISC: precision:   1.23%; recall:  60.62%; FB1:   2.42  168908\r\n              ORG: precision:  16.17%; recall:   5.32%; FB1:   8.00  2078\r\n              PER: precision:   4.88%; recall:   9.09%; FB1:   6.35  12286\r\n\r\nEvaluate model on the valid set\r\nprocessed 51362 tokens with 5942 phrases; found: 50303 phrases; correct: 869.\r\naccuracy:   3.43%; precision:   1.73%; recall:  14.62%; FB1:   3.09\r\n              LOC: precision:   1.58%; recall:   2.94%; FB1:   2.06  3415\r\n             MISC: precision:   1.27%; recall:  59.87%; FB1:   2.48  43568\r\n              ORG: precision:  21.15%; recall:   6.04%; FB1:   9.40  383\r\n              PER: precision:   6.20%; recall:   9.88%; FB1:   7.62  2937\r\n\r\nEvaluate model on the test set\r\nprocessed 46435 tokens with 5648 phrases; found: 45225 phrases; correct: 689.\r\naccuracy:   3.43%; precision:   1.52%; recall:  12.20%; FB1:   2.71\r\n              LOC: precision:   1.59%; recall:   3.24%; FB1:   2.13  3404\r\n             MISC: precision:   1.09%; recall:  59.26%; FB1:   2.13  38275\r\n              ORG: precision:  16.52%; recall:   4.46%; FB1:   7.02  448\r\n              PER: precision:   4.68%; recall:   8.97%; FB1:   6.15  3098\r\n\r\nGenerating plots for the train set\r\nTraceback (most recent call last):\r\n  File \"main.py\", line 250, in <module>\r\n    main()\r\n  File \"main.py\", line 246, in main\r\n    nn.fit()\r\n  File \"/Users/xxx/linux/test/python/nlpdl/NeuroNER/src/neuroner.py\", line 394, in fit\r\n    evaluate.evaluate_model(results, dataset, y_pred, y_true, stats_graph_folder, epoch_number, epoch_start_time, output_filepaths, parameters)\r\n  File \"/Users/xxx/linux/test/python/nlpdl/NeuroNER/src/evaluate.py\", line 239, in evaluate_model\r\n    verbose=verbose)\r\n  File \"/Users/xxx/linux/test/python/nlpdl/NeuroNER/src/evaluate.py\", line 22, in assess_model\r\n    cmap='RdBu')\r\n  File \"/Users/xxx/linux/test/python/nlpdl/NeuroNER/src/utils_plots.py\", line 162, in plot_classification_report\r\n    heatmap(np.array(plotMat), title, xlabel, ylabel, xticklabels, yticklabels, figure_width, figure_height, correct_orientation, cmap=cmap)\r\n  File \"/Users/xxx/linux/test/python/nlpdl/NeuroNER/src/utils_plots.py\", line 112, in heatmap\r\n    show_values(c, fmt=fmt)\r\n  File \"/Users/xxx/linux/test/python/nlpdl/NeuroNER/src/utils_plots.py\", line 36, in show_values\r\n    ax = pc.get_axes()\r\nAttributeError: 'PolyCollection' object has no attribute 'get_axes'\r\n```"},"comment":{"url":"https://api.github.com/repos/Franck-Dernoncourt/NeuroNER/issues/comments/350476313","html_url":"https://github.com/Franck-Dernoncourt/NeuroNER/issues/83#issuecomment-350476313","issue_url":"https://api.github.com/repos/Franck-Dernoncourt/NeuroNER/issues/83","id":350476313,"user":{"login":"JohnGiorgi","id":8917831,"avatar_url":"https://avatars3.githubusercontent.com/u/8917831?v=4","gravatar_id":"","url":"https://api.github.com/users/JohnGiorgi","html_url":"https://github.com/JohnGiorgi","followers_url":"https://api.github.com/users/JohnGiorgi/followers","following_url":"https://api.github.com/users/JohnGiorgi/following{/other_user}","gists_url":"https://api.github.com/users/JohnGiorgi/gists{/gist_id}","starred_url":"https://api.github.com/users/JohnGiorgi/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/JohnGiorgi/subscriptions","organizations_url":"https://api.github.com/users/JohnGiorgi/orgs","repos_url":"https://api.github.com/users/JohnGiorgi/repos","events_url":"https://api.github.com/users/JohnGiorgi/events{/privacy}","received_events_url":"https://api.github.com/users/JohnGiorgi/received_events","type":"User","site_admin":false},"created_at":"2017-12-09T14:54:49Z","updated_at":"2017-12-09T14:54:49Z","author_association":"CONTRIBUTOR","body":"This was asked & solved in #76"}}
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